Proceedings
Authors
| Filter results2 paper(s) found. |
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1. Detection of Weed-Related Anomalies in Sugarcane Fields Using Sentinel-2 ImageryWeed infestation is one of the main causes of yield losses in agricultural systems, particularly in large-scale crops such as sugarcane. Conventional weed management, based on uniform herbicide application, often ignores the spatial variability of infestations, resulting in higher production costs and environmental impacts. In this context, remote sensing and machine learning techniques are recently being used as a solution for automation and precision in crop monitoring. In this study,... R.P. Amaro, F. Amstalden, C. Berro Filho, D.G. Duft |
2. Estimation of Soybean Yield Using Remote Sensing and Soil Physical Attributes in Subsoiled AreasPrecision agriculture has incorporated these sensing and computational modeling technologies as strategic tools for monitoring crop development and estimating yield. In this context, the present study aimed to estimate soybean yield through vegetation indices obtained from satellite images, integrated with soil and plant variables, using artificial intelligence techniques. The experiment was conducted in a commercial field in the municipality of Brejo, Maranhão, in a region with a subhumid... W. Garreto, S. De Almeida, W. Da Silva Sousa, J. Costa Souza |